Convergence of densities of spatial averages of the parabolic Anderson model driven by colored noise

IF 1.1 2区经济学 Q3 BUSINESS, FINANCE

Finance and Stochastics Pub Date : 2022-05-27 DOI:10.1080/17442508.2023.2238954

Sefika Kuzgun, D. Nualart

引用次数: 0

Abstract

In this paper, we present a rate of convergence in the uniform norm for the densities of spatial averages of the solution to the d-dimensional parabolic Anderson model driven by a Gaussian multiplicative noise, which is white in time and has a spatial covariance given by the Riesz kernel. The proof is based on the combination of Malliavin calculus techniques and the Stein's method for normal approximations.

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彩色噪声驱动下抛物型Anderson模型空间平均密度的收敛性

在本文中，我们给出了由高斯乘性噪声驱动的d维抛物型Anderson模型解的空间平均密度的一致范数的收敛速率，该模型在时间上是白色的，并且具有由Riesz核给出的空间协方差。该证明是基于马立文演算技术和斯坦的正态逼近方法的结合。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Finance and Stochastics 管理科学-数学跨学科应用

CiteScore

2.90

自引率

5.90%

发文量

审稿时长

>12 weeks

期刊介绍： The purpose of Finance and Stochastics is to provide a high standard publication forum for research - in all areas of finance based on stochastic methods - on specific topics in mathematics (in particular probability theory, statistics and stochastic analysis) motivated by the analysis of problems in finance. Finance and Stochastics encompasses - but is not limited to - the following fields: - theory and analysis of financial markets - continuous time finance - derivatives research - insurance in relation to finance - portfolio selection - credit and market risks - term structure models - statistical and empirical financial studies based on advanced stochastic methods - numerical and stochastic solution techniques for problems in finance - intertemporal economics, uncertainty and information in relation to finance.